METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by...
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
About this item
Full title
Author / Creator
Kocak, Burak , Akinci D’Antonoli, Tugba , Mercaldo, Nathaniel , Alberich-Bayarri, Angel , Baessler, Bettina , Ambrosini, Ilaria , Andreychenko, Anna E. , Bakas, Spyridon , Beets-Tan, Regina G. H. , Bressem, Keno , Buvat, Irene , Cannella, Roberto , Cappellini, Luca Alessandro , Cavallo, Armando Ugo , Chepelev, Leonid L. , Chu, Linda Chi Hang , Demircioglu, Aydin , deSouza, Nandita M. , Dietzel, Matthias , Fanni, Salvatore Claudio , Fedorov, Andrey , Fournier, Laure S. , Giannini, Valentina , Girometti, Rossano , Groot Lipman, Kevin B. W. , Kalarakis, Georgios , Kelly, Brendan S. , Klontzas, Michail E. , Koh, Dow-Mu , Kotter, Elmar , Lee, Ho Yun , Maas, Mario , Marti-Bonmati, Luis , Müller, Henning , Obuchowski, Nancy , Orlhac, Fanny , Papanikolaou, Nikolaos , Petrash, Ekaterina , Pfaehler, Elisabeth , Pinto dos Santos, Daniel , Ponsiglione, Andrea , Sabater, Sebastià , Sardanelli, Francesco , Seeböck, Philipp , Sijtsema, Nanna M. , Stanzione, Arnaldo , Traverso, Alberto , Ugga, Lorenzo , Vallières, Martin , van Dijk, Lisanne V. , van Griethuysen, Joost J. M. , van Hamersvelt, Robbert W. , van Ooijen, Peter , Vernuccio, Federica , Wang, Alan , Williams, Stuart , Witowski, Jan , Zhang, Zhongyi , Zwanenburg, Alex and Cuocolo, Renato
Publisher
Vienna: Springer Vienna
Journal title
Language
English
Formats
Publication information
Publisher
Vienna: Springer Vienna
Subjects
More information
Scope and Contents
Contents
Purpose
To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies.
Methods
We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated.
Result
In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community.
Conclusion
In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers.
Critical relevance statement
A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning.
Key points
• A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol.
• The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time.
• METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines.
• A web application has been developed to help with the calculation of the METRICS score (
https://metricsscore.github.io/metrics/METRICS.html
) and a repository created to collect feedback from the radiomics community (
https://github.com/metricsscore/metrics
).
Graphical Abstract...
Alternative Titles
Full title
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII
Authors, Artists and Contributors
Author / Creator
Akinci D’Antonoli, Tugba
Mercaldo, Nathaniel
Alberich-Bayarri, Angel
Baessler, Bettina
Ambrosini, Ilaria
Andreychenko, Anna E.
Bakas, Spyridon
Beets-Tan, Regina G. H.
Bressem, Keno
Buvat, Irene
Cannella, Roberto
Cappellini, Luca Alessandro
Cavallo, Armando Ugo
Chepelev, Leonid L.
Chu, Linda Chi Hang
Demircioglu, Aydin
deSouza, Nandita M.
Dietzel, Matthias
Fanni, Salvatore Claudio
Fedorov, Andrey
Fournier, Laure S.
Giannini, Valentina
Girometti, Rossano
Groot Lipman, Kevin B. W.
Kalarakis, Georgios
Kelly, Brendan S.
Klontzas, Michail E.
Koh, Dow-Mu
Kotter, Elmar
Lee, Ho Yun
Maas, Mario
Marti-Bonmati, Luis
Müller, Henning
Obuchowski, Nancy
Orlhac, Fanny
Papanikolaou, Nikolaos
Petrash, Ekaterina
Pfaehler, Elisabeth
Pinto dos Santos, Daniel
Ponsiglione, Andrea
Sabater, Sebastià
Sardanelli, Francesco
Seeböck, Philipp
Sijtsema, Nanna M.
Stanzione, Arnaldo
Traverso, Alberto
Ugga, Lorenzo
Vallières, Martin
van Dijk, Lisanne V.
van Griethuysen, Joost J. M.
van Hamersvelt, Robbert W.
van Ooijen, Peter
Vernuccio, Federica
Wang, Alan
Williams, Stuart
Witowski, Jan
Zhang, Zhongyi
Zwanenburg, Alex
Cuocolo, Renato
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_84735d3b21f949ab8a02d96fb603cc0c
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_84735d3b21f949ab8a02d96fb603cc0c
Other Identifiers
ISSN
1869-4101
E-ISSN
1869-4101
DOI
10.1186/s13244-023-01572-w